The multimodal target detection algorithm has the problem of poor feature fusion ability of different modes, which leads to poor detection accuracy. Therefore, this paper improves and optimizes the MVX-Net algorithm, and proposes an adaptive multi-modal feature fusion algorithm AF-MVX-Net (adaptive fusion). The algorithm is based on the MVX-Net framework, and an adaptive multi-modal feature Fusion module AFM (Adaptation Fusion Module) is added. The module was designed by analyzing the relationship between local and global features to adaptively enhance the weighting of important features in the fused data to improve the effectiveness of multimodal fusion, thus improving detection accuracy. The results of the experimental verification on the KITTI dataset demonstrate that the average 3DAP value of all categories of simple targets has increased by 8.55% to 76.1%. ; For vehicle categories, the value of 3DAP@0.7 increased by 2%; Bicycle category 3DAP@0.5 value increased by 5~6%; The 3DAP@0.5 value of the pedestrian category increased by 10~13%, which effectively improves the detection accuracy of bicycles, pedestrians and vehicles in the automatic driving scenario, so FA-MVX-Net algorithm is proved to be effective.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multimodal target detection algorithm based on adaptive feature fusion


    Contributors:
    Wu, Jinsong (editor) / Ma'aram, Azanizawati (editor) / Li, Yitong (author) / He, Chuchao (author) / Di, Ruohai (author) / Wang, Peng (author) / Sun, Mengyu (author) / Li, Xiaoyan (author)

    Conference:

    Ninth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024) ; 2024 ; Guilin, China


    Published in:

    Proc. SPIE ; 13251


    Publication date :

    2024-08-28





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    A 3D Object Detection Method Based on Cross-Attention Multimodal Feature Fusion

    Tian, Juanxiu / Zhou, Yanping / Peng, Meng et al. | IEEE | 2024


    Spore detection algorithm of wheat powdery mildew based on weight adaptive feature fusion

    Niu, Hao / Wang, Botao | British Library Conference Proceedings | 2022



    Anti-Occlusion UAV Target Detection Based on Attention Feature Fusion

    Zhu, Xiaoyong / Luo, Cai / Lv, Xinrong et al. | IEEE | 2023